US20140032544A1 - Method for refining the results of a search within a database - Google Patents

Method for refining the results of a search within a database Download PDF

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Publication number
US20140032544A1
US20140032544A1 US13/987,997 US201313987997A US2014032544A1 US 20140032544 A1 US20140032544 A1 US 20140032544A1 US 201313987997 A US201313987997 A US 201313987997A US 2014032544 A1 US2014032544 A1 US 2014032544A1
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objects
relevance
relevant
user
search
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US13/987,997
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English (en)
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Eric Mathieu
Cyril March
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Xilopix SAS
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Xilopix SAS
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Assigned to QWANT reassignment QWANT COURT ORDER (SEE DOCUMENT FOR DETAILS). Assignors: XILIPOX
Assigned to QWANT reassignment QWANT COURT ORDER (SEE DOCUMENT FOR DETAILS). Assignors: XILOPIX
Assigned to QWANT reassignment QWANT COURT ORDER (SEE DOCUMENT FOR DETAILS). Assignors: XILOPIX
Abandoned legal-status Critical Current

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    • G06F17/3053—
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2457—Query processing with adaptation to user needs
    • G06F16/24578—Query processing with adaptation to user needs using ranking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/54—Browsing; Visualisation therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/5866—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using information manually generated, e.g. tags, keywords, comments, manually generated location and time information

Definitions

  • the present disclosure relates to a method for refining the results of a search in a database containing a set of objects.
  • a particularly significant example thereof is the development of digital photography, in particular on account of the development of online publishing sites and photo sharing site.
  • one of the leaders among such types of sites exceeded the five billion mark in terms of number of photos posted online and has since then continued to add several thousands more online per day.
  • These digital objects are usually listed in the database in association with key words and/or other technical descriptors (size, resolution, etc). These keywords and descriptors make it possible to perform searches of the database and to return the objects whose keywords match the search criteria entered by a user in a search field.
  • search engines have been primarily designed to enable searching for text within web pages or files, and in particular in associated description texts.
  • the keywords and associated descriptors become considerably more important for enabling an efficient search to be performed followed by a relevant search result being returned.
  • a keyword search has inherent limitations, in particular, for example due to the existence in the human language of synonyms, homonyms, hierarchy in terms, and degree of accuracy.
  • Such a process for carrying out a search is, however, not particularly easy for the user and may, on certain search engines, amount to requiring almost programming level skills to write a query, while not knowing whether this query could be correctly interpreted by the engine and lead to the desired result.
  • the present disclosure provides a method for refining the results of a search for objects within at least one database containing at least one set of objects each associated with at least one descriptor, the said method comprising steps of:
  • object refers to any digital object that can be stored in a database. As stated above, it may in particular be photographs, as well as other types of files including audio, video, documents, etc.
  • descriptor used is not limited.
  • descriptor obviously includes descriptors such as keywords, but it could refer also to more technical descriptors referencing textures, materials, color profiles, definition, etc. It could also be semantic descriptors established based on a thesaurus.
  • the nature of the descriptors is generally not limited and they may be adapted depending upon the objects that are referenced in the relevant databases, and searched.
  • weights can be assigned to different descriptors, in particular as a function of their origin, context, and situation in relation to all of the other descriptors.
  • the descriptors from a thesaurus and therefore having a standardized, uniform and structured nature, may have greater weight than that of the keyword type descriptors that have been assigned by the users of a photo sharing site themselves.
  • the method of the present disclosure allows for the user to overcome to some extent issues arising from the language of textual descriptors used.
  • the user by using the method according to the present disclosure to refine the search results can also assign a weight in a transparent manner to descriptors and keywords in the foreign language associated with the object.
  • the search could therefore ultimately become refined on the basis of key words in a foreign language, or at least by taking them into account, the foreign language being one that the user does not necessarily understand and which they would not have entered directly into a text based search engine.
  • the set of objects initially presented to the user corresponds to all or part of the objects resulting from an initial search, in particular by keyword, in the database or databases. Quite obviously, all modes of initial search that allow for generating a first set of objects are possible.
  • a conventional search using a text field and an entry of words by the user one can imagine a selection of objects directly from geographic coordinates on a map, or even a first photo that would, for example, be analyzed in order to extract therefrom search parameters, etc.
  • search in the database or databases may be performed in an internal database, but also on external databases hosted on remote specialized sites, for example.
  • the objects of the set of objects initially presented to the user are presented in a defined order when obtaining said set of objects, in particular in an order of relevance in relation to the initial search, this relevance can in particular be defined by a search algorithm.
  • this relevance can in particular be defined by a search algorithm.
  • the conventional search engines frequently associate a relevance index to their search results.
  • the order of relevance and initial presentation may be defined in an ad hoc manner in order to, for example, maximize the number of different objects initially presented so as to allow the widest possible choice to the user for their first refinement process and eventually for the subsequent ones.
  • the weights assigned to the descriptors of objects considered to be non-relevant and the weights assigned to the descriptors of the objects considered to be relevant have opposite signs, and more particularly, they have respectively negative and positive signs.
  • the absolute values of the weights assigned to the descriptors of the objects considered to be relevant and/or non-relevant are equal.
  • the weight assigned to the descriptors of the objects considered to be relevant have an absolute value that is different, and in particular higher, than the weight assigned to the descriptors of the objects considered to be non-relevant.
  • the values of the weights assigned to the descriptors of the objects considered to be relevant and/or non-relevant may be different for each object signaled.
  • the value of the weights assigned to the descriptors of the objects considered to be relevant and/or non-relevant is a function of their initial order of priority.
  • a coefficient could be applied to a value of standard weight. For example, an object considered to be relevant to 90% par the search engine that carried out the initial search could be found to be attributed 90% of the value of the reference weight if this object is considered to be relevant by the user.
  • the means for signaling the relevance and/or non-relevance of an object presented consists of the means suitable for signaling different degrees of relevance and/or non-relevance that allow for, in particular the assigning of a different weight according to the degree of relevance and/or non-relevance signaled.
  • a web page including buttons to be used to report that an object is, for example, “very relevant” (first degree), “relevant” (second degree), “somewhat relevant” (third degree) “not relevant” (fourth degree) and “off topic” (fifth degree).
  • the result objects are presented in the form of previews, thumbnails and/or excerpts.
  • the objects contained in the database include photographs, video, and or audio objects. There may also be other types of documents, text files, etc.
  • the relevance index is initialized to the same value for each result object, in particular to zero.
  • the relevance index is initialized to different values for all or part of the result objects, in particular as a function of the initial order of presentation and, as appropriate, of a relevance value returned by the initial search.
  • all or part of the descriptors of the most relevant objects returned feed a new search in the database.
  • FIG. 1 is a screen shot of a website that has practically implemented the method according to the present disclosure, at the level of the first step presenting to a user the results of an initial search by keyword;
  • FIG. 2 is a screen shot of the website in FIG. 1 wherein a user has signaled a photo that they consider to be relevant to their search;
  • FIG. 3 is a screen shot of the website in FIG. 1 wherein a user has signaled a photo that they consider to be non-relevant to their search;
  • FIG. 4 is a screen shot after the triggering of the step of refining the search by the user
  • FIG. 5 is a screen shot of the website in FIG. 1 showing the result of the step of refining carried out on the basis of the signals indicative of relevance and non-relevance by the user;
  • FIG. 6 is a flowchart schematically illustrating the practical operation of the process illustrated in FIGS. 1 to 5 .
  • FIGS. 1 to 5 show screen shots of a web site that has practically implemented the method according to the present disclosure on a search for photos of car headlights.
  • FIG. 1 shows a first step 101 in which a set of thumbnails of photos P 1 to P 14 is presented to the user.
  • This set of photos P 1 to P 14 has been obtained through an initial search by keyword in one or more databases of photos.
  • the keyword in French “phare” was used by the user in order to define the search and keyed in into a search field R of the page.
  • the search field R serves as interface with the user and feeds a search engine that may be internal or external to the site, in the databases of photos.
  • a search engine that may be internal or external to the site, in the databases of photos.
  • Such data bases include a great number of photos and associate therewith various descriptors for the purposes of facilitating further searches.
  • descriptors include in particular lists of keywords, but may also be parameters specific to the photo (photograph used, technical data, color profile, etc).
  • the search engine therefore returns the results of its search algorithm and presents them to the user in the form of fourteen thumbnail photographs P 1 to P 14 .
  • the fourteen photographs presented to the user do not necessarily correspond to the full results of the initial search and it is quite possible to choose to present to the user only a part of the results, for example the first thousand photographs returned.
  • the photographs P 1 , P 2 , P 4 , P 5 , P 7 , P 8 , P 9 , P 11 , P 12 refer to photographs of coastal lighthouses for navigation.
  • Each photo is associated, in the database that contains it or in another database, with one or more descriptors.
  • photographs P 1 to P 14 are each presented to the user in association with a clickable image I 1 representing a ‘check mark’ of validation and a clickable image 12 representing a ‘cross out mark’ of rejection.
  • clickable images are associated with computing functions recording the user's choice and constituting the means for said user to signal the relevance (check mark) and/or non-relevance (cross out mark) of each photograph in relation to their actual search.
  • the user then proceeds during a step 102 to the signaling of the photographs that they consider to be relevant and/or non-relevant.
  • FIG. 2 is a screen shot showing that the user signaled that the photograph P 14 was relevant to their actual search.
  • a message M 1 informs them that their signaling has properly been taken into consideration by the website or software.
  • FIG. 3 is a screen shot showing that the user has signaled that the photograph P 4 was not relevant to their actual search since it shows a coastal lighthouse.
  • a message M 2 informs them that their signaling has properly been taken into consideration by the website or software.
  • the messages M 1 and M 2 are displayed in the form of “pop-up” messages (display of an overlay window). It is quite evident that these messages may be signaled to the user in other forms, in particular, by a grouping together of the images selected, a display in a sidebar, the setting up of virtual carts for the images selected as relevant and non-relevant, etc.
  • the refining process can also take place in real time based on interactions of the user, this would however, require greater processing resources and support of a remote server in particular.
  • the processing steps are transparent to the user.
  • a weight P is associated with each descriptor associated with each image signaled by the user.
  • the weight P is assigned a negative sign if the image has been signaled as non-relevant and a positive sign if the image has been signaled as relevant.
  • the photograph P 4 which has a descriptor “phare” associated, has been signaled as non-relevant and the photograph P 14 , which has two descriptors “phare” and “voiture” associated, has been signalled as relevant.
  • the descriptor “phare” is assigned a weight ⁇ P on account of the non-relevance signaled for the photograph P 4 and is assigned a weight +P on account of the relevance signaled for the photograph P 14 .
  • the descriptor “voiture” is assigned a weight +P on account of the relevance signaled for the photograph P 14 .
  • a resultant of the weights assigned to each descriptor of the set of images P 1 to P 14 is calculated during the course of a step 104 .
  • the descriptor “phare” thus gets an overall weight of null, while the descriptor “voiture” gets an overall weight equal to +P.
  • the resultant is the set of descriptors of the photographs P 1 to P 4 assigned their respective weights as calculated previously.
  • a relevance index is associated with each photo P 1 to P 14 and initialized to zero during a step 105 .
  • Each photograph P 1 to P 14 therefore has the same priority and relevance.
  • a step 106 is then carried out to compare each photograph P 1 to P 14 with the resultant of the weights of the descriptors.
  • each descriptor of the photograph P 1 to P 14 is compared to the resultant, and the priority index is increased or decreased by the weight of the descriptor in the said resultant.
  • the photograph P 1 showing a coastal lighthouse, and having only the descriptor “phare”, gets its priority index increased by the weight of the descriptor “phare” in the resultant, that is by zero. Its priority index therefore remains at zero. The same holds true for the photograph P 2 .
  • the photograph P 3 however shows car headlights. As mentioned earlier, it is associated with two descriptors “phare” and “voiture”. For the descriptor “phare”, its index does not change, since the weight of this descriptor is null. However, for the descriptor “voiture”, its priority index is increased by the weight of the descriptor “voiture” in the resultant, that is by +P. Its priority index thus becomes +P.
  • FIG. 5 shows a screen shot presenting the final rearrangement where only photographs of car headlights are properly presented.
  • FIG. 5 also shows the photos that were not present on the initial presentation screen. Indeed, it is quite possible to select a batch of initial photos that is larger than the batch of fourteen photographs presented, with some photographs then being hidden from the user. However, they are present in the initial selection and are taken into consideration for the implementation of the process. Therefore they also receive a relevance index that changes their order in the selection. In the end, they may thus be found amongst the first fourteen photos, and therefore be presented to the user.
  • the user can then perform a new refinement of their search, particularly if new photos have been presented to them (step 108 ) or stop their search (step 109 ).
  • This may in particular include the provision of additional means of signaling, for example a “neutral” button in addition to the means used to signal the characteristics of relevance and/or non-relevance.

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  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Library & Information Science (AREA)
  • Computational Linguistics (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • User Interface Of Digital Computer (AREA)
US13/987,997 2011-03-23 2013-09-23 Method for refining the results of a search within a database Abandoned US20140032544A1 (en)

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FR1152383A FR2973134B1 (fr) 2011-03-23 2011-03-23 Procede pour affiner les resultats d'une recherche dans une base de donnees
FR11/52383 2011-03-23
PCT/FR2012/050576 WO2012127168A1 (fr) 2011-03-23 2012-03-19 Procédé pour affiner les résultats d'une recherche dans une base de données

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EP (2) EP2689351A1 (de)
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CN103518198A (zh) 2014-01-15
FR2973134A1 (fr) 2012-09-28
KR101980219B1 (ko) 2019-08-28
WO2012127168A1 (fr) 2012-09-27
EP3627353A1 (de) 2020-03-25
RU2013146871A (ru) 2015-04-27
FR2973134B1 (fr) 2015-09-11
KR20140027173A (ko) 2014-03-06
EP2689351A1 (de) 2014-01-29
RU2613039C2 (ru) 2017-03-14

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